Predicting the individual best saddle height of bicycle based on electromyography and Fuzzy Inference

Recently, various social issues, such as global warming problem, economical abrupt move, and diseases associated with adult lifestyle habits, are reported. Against them, the role of bicycle has been reviewed as one of effective solutions. In fact, many types of bicycles have been developed and have been widely used in our daily life. Though commercially available bicycles have various size of frame for user's physical size, and the positions both of a saddle and a handle can be modified, but there is a lack of interests in the importance of bicycle position as a shared awareness. Provision of proper riding posture for riders based on their physical properties would enable to improve the efficiency of cycling exercise, and to prevent some chronic pains occurred in places of body. To establish an optimization method of bicycle position based on individual biomedical information, this study focuses on the importance of bicycle position, especially we address to search a suitable saddle height corresponding to user's physical features and properties. This paper firstly develops an automatic saddle height control system, and secondly supposes an evaluation standard of cycling exercise based on electromyographic signals of rider's leg during cycling exercise, and an optimization method of saddle height by using fast Fourier transformation (FFT), principle component analysis (PCA), and fuzzy inference. This paper shows firstly the concepts of the evaluation standard we have defined for rider's pedaling performance with some experimental results, and introduces a fuzzy control system for automatic saddle height control.